Experiential Modes of Game Play

Robert Appelman's paper presents the Experiential Mode Framework (EMF), a standardized methodology developed at the Virtual Xperience Lab at Indiana University for analyzing how people play video games. The framework addresses the difficulty of quantifying game play by separating two analytical perspectives: the Player Experience (PX), encompassing cognition, metacognition, choice, and action, and the Game Structure (GS), encompassing content, environment, and affordances. The approach draws on Robert Yin's multiple case study methodology, treating each play session as a distinct case and comparing patterns across sessions rather than aggregating results into statistical scores.

The methodology proceeds in four phases: pre-play analysis of player demographics and game structure, data capture through video recording, observation, and interviews, pattern-based analysis, and summative conclusions. Demographic data includes age, gender, education, platform preferences, and weekly play hours, which are used to rank players as experts or novices across multidimensional skill criteria. Spatial data is recorded on coordinate grids, and temporal data is logged in seconds, with observations entered onto a standardized log sheet.

The paper illustrates the framework through several observational cases, including a novice player struggling with an unfamiliar PC interface in Syberia II, a Shrek 2 player whose performance improved after encountering explicit goal information, a novice girl whose enjoyment of Halo rose when she could freely ask a friend for help, and a comparison of expert gamers and college athletes in Madden NFL 2006 in which athletes performed better in team-building decisions. These cases are offered as support for four propositions about learning, enjoyment, prior knowledge, and just-in-time social interaction. The author frames the work as establishing baseline empirical data and methodology for serious game design, particularly for high-stakes training contexts.